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  1. To present an approach that autonomously identifies and selects a self-selective optimal target for the purpose of enhancing learning efficiency to segment infected regions of the lung from chest computed tomo...

    Authors: Peng Du, Xiaofeng Niu, Xukun Li, Chiqing Ying, Yukun Zhou, Chang He, Shuangzhi Lv, Xiaoli Liu, Weibo Du and Wei Wu
    Citation: BMC Bioinformatics 2023 24:332
  2. Over the past several decades, metrics have been defined to assess the quality of various types of models and to compare their performance depending on their capacity to explain the variance found in real-life...

    Authors: Evgueni Jacob, Angélique Perrillat-Mercerot, Jean-Louis Palgen, Adèle L’Hostis, Nicoletta Ceres, Jean-Pierre Boissel, Jim Bosley, Claudio Monteiro and Riad Kahoul
    Citation: BMC Bioinformatics 2023 24:331
  3. The study of de novo variation is important for assessing biological characteristics of new variation and for studies related to human phenotypes. Software programs exist to call de novo variants and programs ...

    Authors: Tychele N. Turner
    Citation: BMC Bioinformatics 2023 24:330
  4. Alcohol use disorder (AUD) causes significant morbidity, mortality, and injuries. According to reports, approximately 5% of all registered deaths in Denmark could be due to AUD. The problem is compounded by th...

    Authors: Ali Ebrahimi, Uffe Kock Wiil, Ruben Baskaran, Abdolrahman Peimankar, Kjeld Andersen and Anette Søgaard Nielsen
    Citation: BMC Bioinformatics 2023 24:329
  5. Longitudinal data on key cancer outcomes for clinical research, such as response to treatment and disease progression, are not captured in standard cancer registry reporting. Manual extraction of such outcomes...

    Authors: Haitham A. Elmarakeby, Pavel S. Trukhanov, Vidal M. Arroyo, Irbaz Bin Riaz, Deborah Schrag, Eliezer M. Van Allen and Kenneth L. Kehl
    Citation: BMC Bioinformatics 2023 24:328
  6. The Earth Biogenome Project has rapidly increased the number of available eukaryotic genomes, but most released genomes continue to lack annotation of protein-coding genes. In addition, no transcriptome data i...

    Authors: Tomáš Brůna, Heng Li, Joseph Guhlin, Daniel Honsel, Steffen Herbold, Mario Stanke, Natalia Nenasheva, Matthis Ebel, Lars Gabriel and Katharina J. Hoff
    Citation: BMC Bioinformatics 2023 24:327
  7. Here we present scSNPdemux, a sample demultiplexing pipeline for single-cell RNA sequencing data using natural genetic variations in humans. The pipeline requires alignment files from Cell Ranger (10× Genomics...

    Authors: John K. L. Wong, Lena Jassowicz, Christel Herold-Mende, Martina Seiffert, Jan-Philipp Mallm, Peter Lichter and Marc Zapatka
    Citation: BMC Bioinformatics 2023 24:326
  8. There are countless possibilities for drug combinations, which makes it expensive and time-consuming to rely solely on clinical trials to determine the effects of each possible drug combination. In order to sc...

    Authors: Jing Chen, Lianlian Wu, Kunhong Liu, Yong Xu, Song He and Xiaochen Bo
    Citation: BMC Bioinformatics 2023 24:325
  9. Understanding the impact of gene interactions on disease phenotypes is increasingly recognised as a crucial aspect of genetic disease research. This trend is reflected by the growing amount of clinical researc...

    Authors: Alexandre Renaux, Chloé Terwagne, Michael Cochez, Ilaria Tiddi, Ann Nowé and Tom Lenaerts
    Citation: BMC Bioinformatics 2023 24:324
  10. Prediction of drug–target interaction (DTI) is an essential step for drug discovery and drug reposition. Traditional methods are mostly time-consuming and labor-intensive, and deep learning-based methods addre...

    Authors: Ying Qian, Xinyi Li, Jian Wu and Qian Zhang
    Citation: BMC Bioinformatics 2023 24:323
  11. The impact of a perturbation, over-expression, or repression of a key node on an organism, can be modelled based on a regulatory and/or metabolic network. Integration of these two networks could improve our gl...

    Authors: Sophie Le Bars, Mathieu Bolteau, Jérémie Bourdon and Carito Guziolowski
    Citation: BMC Bioinformatics 2023 24(Suppl 1):321

    This article is part of a Supplement: Volume 24 Supplement 1

  12. Quantitative analysis of neurite growth and morphology is essential for understanding the determinants of neural development and regeneration, however, it is complicated by the labor-intensive process of measu...

    Authors: Joseph T. Vecchi, Sean Mullan, Josue A. Lopez, Madeline Rhomberg, Annamarie Yamamoto, Annabelle Hallam, Amy Lee, Milan Sonka and Marlan R. Hansen
    Citation: BMC Bioinformatics 2023 24:320
  13. Single-cell RNA sequencing (scRNA-seq) technology has enabled assessment of transcriptome-wide changes at single-cell resolution. Due to the heterogeneity in environmental exposure and genetic background acros...

    Authors: Yunqing Liu, Jiayi Zhao, Taylor S. Adams, Ningya Wang, Jonas C. Schupp, Weimiao Wu, John E. McDonough, Geoffrey L. Chupp, Naftali Kaminski, Zuoheng Wang and Xiting Yan
    Citation: BMC Bioinformatics 2023 24:318

    The Correction to this article has been published in BMC Bioinformatics 2023 24:394

  14. Transposable elements (TEs) are short, mobile DNA elements that are known to play important roles in the genomes of many eukaryotic species. The identification and categorization of these elements is a critica...

    Authors: Shelvasha Burkes-Patton, Elizabeth A. Cooper and Jessica Schlueter
    Citation: BMC Bioinformatics 2023 24:317
  15. Biologists are faced with an ever-changing array of complex software tools with steep learning curves, often run on High Performance Computing platforms. To resolve the tradeoff between analytical sophisticati...

    Authors: Graham Alvare, Abiel Roche-Lima and Brian Fristensky
    Citation: BMC Bioinformatics 2023 24:316
  16. Two types of non-invasive, radiation-free, and inexpensive imaging technologies that are widely employed in medical applications are ultrasound (US) and infrared thermography (IRT). The ultrasound image obtain...

    Authors: Na Zhang, Juan Liu, Yu Jin, Wensi Duan, Ziling Wu, Zhaohui Cai and Meng Wu
    Citation: BMC Bioinformatics 2023 24:315
  17. Since the introduction of next-generation sequencing (NGS) techniques, whole-exome sequencing (WES) and whole-genome sequencing (WGS) have not only revolutionized research, but also diagnostics. The gradual sw...

    Authors: Fréderique Boeykens, Sofie F. M. Bhatti, Luc Peelman and Bart J. G. Broeckx
    Citation: BMC Bioinformatics 2023 24:305
  18. Integrating multi-omics data is fast becoming a powerful approach for predicting disease progression and treatment outcomes. In light of that, we introduce a modified version of the NetRank algorithm, a networ...

    Authors: Ali Al-Fatlawi, Eka Rusadze, Alexander Shmelkin, Negin Malekian, Cigdem Ozen, Christian Pilarsky and Michael Schroeder
    Citation: BMC Bioinformatics 2023 24:304
  19. The growing power and ever decreasing cost of RNA sequencing (RNA-Seq) technologies have resulted in an explosion of RNA-Seq data production. Comparing gene expression values within RNA-Seq datasets is relativ...

    Authors: Alvin Farrel, Peng Li, Sharon Veenbergen, Khushbu Patel, John M. Maris and Warren J. Leonard
    Citation: BMC Bioinformatics 2023 24:303
  20. Single-cell RNA sequencing (scRNA-seq) enables the high-throughput profiling of gene expression at the single-cell level. However, overwhelming dropouts within data may obscure meaningful biological signals. V...

    Authors: Yi Cheng, Xiuli Ma, Lang Yuan, Zhaoguo Sun and Pingzhang Wang
    Citation: BMC Bioinformatics 2023 24:302
  21. The identification of tumor T cell antigens (TTCAs) is crucial for providing insights into their functional mechanisms and utilizing their potential in anticancer vaccines development. In this context, TTCAs a...

    Authors: Phasit Charoenkwan, Nalini Schaduangrat and Watshara Shoombuatong
    Citation: BMC Bioinformatics 2023 24:301
  22. Modern genome sequencing leads to an ever-growing collection of genomic annotations. Combining these elements with a set of input regions (e.g. genes) would yield new insights in genomic associations, such as ...

    Authors: Sven Berres, Jörg Gromoll, Marius Wöste, Sarah Sandmann and Sandra Laurentino
    Citation: BMC Bioinformatics 2023 24:300
  23. Protein biomarkers of cancer progression and response to therapy are increasingly important for improving personalized medicine. Advanced quantitative pathology platforms enable measurement of protein expressi...

    Authors: Misung Yi, Tingting Zhan, Amy R. Peck, Jeffrey A. Hooke, Albert J. Kovatich, Craig D. Shriver, Hai Hu, Yunguang Sun, Hallgeir Rui and Inna Chervoneva
    Citation: BMC Bioinformatics 2023 24:298
  24. Statistical correlation analysis is currently the most typically used approach for investigating the risk factors of type 2 diabetes mellitus (T2DM). However, this approach does not readily reveal the causal r...

    Authors: Xiu-E. Gao, Jian-Gang Hu, Bo Chen, Yun-Ming Wang and Sheng-Bin zhou
    Citation: BMC Bioinformatics 2023 24:296
  25. To understand genome evolution in a group of microbes, we need to know the timing of events such as duplications, deletions and horizontal transfers. A common approach is to perform a gene-tree / species-tree ...

    Authors: Nuo Liu, Tonatiuh A. Gonzalez, Jacob Fischer, Chan Hong, Michelle Johnson, Ross Mawhorter, Fabrizia Mugnatto, Rachael Soh, Shifa Somji, Joseph S. Wirth, Ran Libeskind-Hadas and Eliot C. Bush
    Citation: BMC Bioinformatics 2023 24:295
  26. Identifying variants associated with diseases is a challenging task in medical genetics research. Current studies that prioritize variants within individual genomes generally rely on known variants, evidence f...

    Authors: Șenay Kafkas, Marwa Abdelhakim, Mahmut Uludag, Azza Althagafi, Malak Alghamdi and Robert Hoehndorf
    Citation: BMC Bioinformatics 2023 24:294
  27. The accelerating pace of biomedical publication has made it impractical to manually, systematically identify papers containing specific information and extract this information. This is especially challenging ...

    Authors: Adam J. H. Newton, David Chartash, Steven H. Kleinstein and Robert A. McDougal
    Citation: BMC Bioinformatics 2023 24:292
  28. The rapid expansion of Whole-Genome Sequencing has revolutionized the fields of clinical and food microbiology. However, its implementation as a routine laboratory technique remains challenging due to the grow...

    Authors: Irene Ortega-Sanz, José A. Barbero-Aparicio, Antonio Canepa-Oneto, Jordi Rovira and Beatriz Melero
    Citation: BMC Bioinformatics 2023 24:291
  29. Cancer subtype classification is helpful for personalized cancer treatment. Although, some approaches have been developed to classifying caner subtype based on high dimensional gene expression data, it is diff...

    Authors: Junwei Luo, Yading Feng, Xuyang Wu, Ruimin Li, Jiawei Shi, Wenjing Chang and Junfeng Wang
    Citation: BMC Bioinformatics 2023 24:289
  30.  PacBio high fidelity (HiFi) sequencing reads are both long (15–20 kb) and highly accurate (> Q20). Because of these properties, they have revolutionised genome assembly leading to more accurate and contiguous...

    Authors: Marcela Uliano-Silva, João Gabriel R. N. Ferreira, Ksenia Krasheninnikova, Giulio Formenti, Linelle Abueg, James Torrance, Eugene W. Myers, Richard Durbin, Mark Blaxter and Shane A. McCarthy
    Citation: BMC Bioinformatics 2023 24:288
  31. Next-generation sequencing technologies yield large numbers of genetic alterations, of which a subset are missense variants that alter an amino acid in the protein product. These variants can have a potentiall...

    Authors: Kobe Janssen, Ramon Duran-Romaña, Guy Bottu, Mainak Guharoy, Alexander Botzki, Frederic Rousseau and Joost Schymkowitz
    Citation: BMC Bioinformatics 2023 24:287
  32. Integration site (IS) analysis is a fundamental analytical platform for evaluating the safety and efficacy of viral vector based preclinical and clinical Gene Therapy (GT). A handful of groups have developed s...

    Authors: Aimin Yan, Cristina Baricordi, Quoc Nguyen, Luigi Barbarossa, Mariana Loperfido and Luca Biasco
    Citation: BMC Bioinformatics 2023 24:286

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